We propose a global geomagnetic field model for the last 14 thousand years, based on thermoremanent records. We call the model ArchKalmag14k. ArchKalmag14k is constructed by modifying recently proposed algorithms, based on space‐time correlations. Due to the amount of data and complexity of the model, the full Bayesian posterior is numerically intractable. To tackle this, we sequentialize the inversion by implementing a Kalman‐filter with a fixed time step. Every step consists of a prediction, based on a degree dependent temporal covariance, and a correction via Gaussian process regression. Dating errors are treated via a noisy input formulation. Cross correlations are reintroduced by a smoothing algorithm and model parameters are inferred from the data. Due to the specific statistical nature of the proposed algorithms, the model comes with space and time‐dependent uncertainty estimates. The new model ArchKalmag14k shows less variation in the large‐scale degrees than comparable models. Local predictions represent the underlying data and agree with comparable models, if the location is sampled well. Uncertainties are bigger for earlier times and in regions of sparse data coverage. We also use ArchKalmag14k to analyze the appearance and evolution of the South Atlantic anomaly together with reverse flux patches at the core‐mantle boundary, considering the model uncertainties. While we find good agreement with earlier models for recent times, our model suggests a different evolution of intensity minima prior to 1650 CE. In general, our results suggest that prior to 6000 BCE the data is not sufficient to support global models. Plain Language Summary We use data of archeological and volcanic origin from the last 14 thousand years to construct a global geomagnetic field model. We call the model ArchKalmag14k. The database is uneven in space, with significantly more records in the Northern hemisphere and multiple clusters. Further, the number of available records decreases in time with a distinct drop 6000 BCE. Previous studies introduced a modeling method that was adapted to this inhomogeneities, but could not be applied to the whole database for computational reasons. To tackle this, we modify the method and implement an approach which handles only a number of records at a time. Relations between the individual steps are reintroduced later in the algorithm. Uncertainties in the data and in their ages contribute to estimating reasonable model uncertainties. The model parameters are inferred from the data. ArchKalmag14k shows less variation on a global scale than comparable models. On a local scale, predictions represent the underlying data and agree with comparable models, if the location is covered well by data. Uncertainties are bigger for times and regions of sparse data coverage. The results suggest that prior to 6000 BCE the data is not sufficient to support global models. Key Points We propose a new global geomagnetic field model for the Holocene based on thermoremanent records Existing algorithms based on space‐time correlation are modified by sequentialization via a Kalman‐filter and smoothing The results suggest that prior to 6000 BCE the data is not sufficient to support global models